煤矿安全2024，Vol.55Issue(1)：167-175,9.DOI:10.13347/j.cnki.mkaq.20221973
矿区沉陷DEM多重滤波方法研究
Research on DEM multiple filtering method for mining subsidence
摘要
Abstract
Aiming at the problems of long cycle time and large workload of traditional surface movement monitoring methods,the method of acquiring ground point clouds and constructing subsidence DEM through UAV LiDAR and point cloud filtering enables surface subsidence monitoring fast and efficient.Because of the subsidence DEM models constructed by existing point cloud filter-ing and interpolation algorithms still cover noise,which limits the popularity of this technology in mining areas,therefore,it is signi-ficant to further study the removal method of subsidence DEM noise,compare and analyze the multiple filtering and classical filter-ing techniques.Experimental analysis results show that the median filter combined with Wiener filter has the best denoising effect among several denoising methods,which can keep the details of the subsidence basin and meet the basic requirements of surface de-formation monitoring in mining areas.关键词
无人机LiDAR/地表沉陷/点云滤波/沉陷DEM/多重滤波Key words
unmanned aerial vehicle LiDAR/surface subsidence/point cloud filtering/subsidence DEM/multi-filtering分类
矿业与冶金引用本文复制引用
姚顽强,蒙延斌,郑俊良,薛志强..矿区沉陷DEM多重滤波方法研究[J].煤矿安全,2024,55(1):167-175,9.基金项目
国家自然科学基金资助项目(42201484) （42201484）
